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GroupOrder
int32
384
447
GroupIndex
int32
1
20.2k
AdjMatrixNonZerEnt
large_stringlengths
4.45k
35.1k
EdgeFeatures
large_stringclasses
65 values
MinNumOfGens
int16
1
7
IsAbelian
bool
2 classes
IsNilpotent
bool
2 classes
IsSimple
bool
2 classes
IsPerfect
bool
1 class
IsSolvable
bool
2 classes
IsMonolithic
bool
2 classes
IsCyclic
bool
2 classes
384
1
[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 2], [1, 9], [1, 10], [1, 11], [1, 12], [1, 13], [1, 14], [1, 15], [2, 3], [2, 9], [2, 16], [2, 17], [2, 18], [2, 19], [2, 20], [2, 21], [3, 4], [3, 10], [3, 16], [3, 22], [3, 23], [3, 24], [3, 25], [3, 26], [4, 5], [4, 11], [4, 17], [4, 22], [4, 27], ...
[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 1], [1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0], [0, 0, ...
2
false
false
false
false
true
false
false
384
2
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 3], [1, 9], [1, 10], [1, 11], (...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
1
true
true
false
false
true
false
true
384
3
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 9], [1, 10], [1, 11], [1, 12],(...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
false
false
384
4
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 9], [1, 10], [1, 11], [1, 12],(...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
true
false
384
5
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 9], [1, 10], [1, 11], [1, 12],(...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
true
false
384
6
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 9], [1, 10], [1, 11], [1, 12],(...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
true
false
384
7
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 3], [1, 9], [1, 10], [1, 11], (...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
false
false
384
8
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 3], [1, 9], [1, 10], [1, 11], (...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
false
false
384
9
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 0], [1, 9], [1, 10], [1, 11], (...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
false
false
384
10
"[[0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [1, 7], [1, 9], [1, 10], [1, 11], (...TRUNCATED)
"[[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0(...TRUNCATED)
2
false
false
false
false
true
false
false
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Cayley Graphs — orders 384–447

This dataset contains Cayley graphs of finite groups: one row per group, covering groups whose order is between 384 and 447. Each graph is the Cayley graph built from the group's minimal generating set (see Provenance below).

  • Rows (groups): 21,814
  • Group orders covered: 384–447 (64 distinct orders)
  • Task: binary graph classification (default label: IsMonolithic).

About the CayleyNet collection

This dataset is part of a census of 131,406 Cayley graphs covering every finite group of order at most 767 (except order 512), built to study how finite-group structure is reflected in the network geometry of Cayley graphs. Each group is recorded with exact algebraic property labels alongside a broad collection of graph, cycle, distance, and spectral statistics. The census provides benchmarks for predicting group properties directly from graph data — comparing classical models, an MLP, and graph neural networks (GIN/GCN) — and contributes new OEIS sequences for monolithic groups and for groups generated by at most 3, 4, and 5 elements.

Code: https://github.com/Engrima18/CayleyNet

Columns

Column Type Description
GroupOrder int32 Order of the finite group (first entry of the GAP SmallGroup id).
GroupIndex int32 Index of the group among all groups of that order (second entry of the GAP SmallGroup id).
AdjMatrixNonZerEnt large_string Directed edge list of the Cayley graph as a JSON-style nested list [[src, dst], ...]; nodes are 0-indexed group elements.
EdgeFeatures large_string One-hot generator matrix of shape [num_edges, num_generators]; row e indicates which generator produced edge e.
MinNumOfGens int16 Size of a minimal generating set of the group.
IsAbelian bool Whether the group is abelian.
IsNilpotent bool Whether the group is nilpotent.
IsSimple bool Whether the group is simple.
IsPerfect bool Whether the group is perfect (G = [G, G]).
IsSolvable bool Whether the group is solvable.
IsMonolithic bool Whether the group is monolithic, i.e. has a unique minimal normal subgroup. Primary classification label.
IsCyclic bool Whether the group is cyclic.

Group-property / label balance

Column # True % True
IsAbelian 139 0.64%
IsNilpotent 2,589 11.87%
IsSimple 10 0.05%
IsPerfect 0 0.00%
IsSolvable 21,813 100.00%
IsMonolithic 157 0.72%
IsCyclic 64 0.29%

Numeric column statistics

Column Min Mean Max Nulls
GroupOrder 384 386.8 447 0
GroupIndex 1 9,341 20,169 0
MinNumOfGens 1 3.636 7 0
NumEdges 389 3,032 3,072 0

Parsing the list-valued columns

AdjMatrixNonZerEnt and EdgeFeatures are stored as strings holding a JSON-style nested list. Decode them with:

import ast
edges = ast.literal_eval(row["AdjMatrixNonZerEnt"])   # [[src, dst], ...]
edge_feats = ast.literal_eval(row["EdgeFeatures"])    # one-hot [E, n_gens]

Provenance

  • Generated with GAP / SageMath and NetworkX (scripts/generate_data.py).
  • Distributed as typed Parquet: the source Id is split into GroupOrder and GroupIndex, and integer statistics are stored as nullable integers.

Usage

from datasets import load_dataset

ds = load_dataset("Enrico18/cayley-graphs-384-to-447", split="train")
print(ds[0])

License

MIT — © 2025 Enrico Grimaldi.

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